Metrics & A/B Test Design Trainer

Pro v1.0.0 1 view

Interactive PM interview practice for metrics selection and A/B test design with Python-calculated statistical rigor and detailed feedback.

What You Get

Get realistic PM interview practice with actual statistical calculations, detailed scoring across multiple dimensions, and improved test designs showing professional PM format.

The Problem

PM interview candidates struggle with metrics selection and A/B test design questions because they lack practice combining statistical rigor with practical product judgment. Most resources teach concepts in isolation without realistic scenarios or feedback on actual calculations.

The Solution

Generate realistic product scenarios (checkout optimization, feature launches, engagement features) requiring complete A/B test design or metrics framework. Collect user's design, then evaluate with Python-calculated sample sizes and statistical requirements. Provide structured feedback scoring metric selection, statistical rigor, variant design, and practical PM judgment. Include improved test design demonstrating professional PM format with all calculated values.

How It Works

  1. 1 Generate realistic product scenario with current metrics, baselines, and business goals
  2. 2 Collect user's complete test design including hypothesis, metrics, sample size estimate, and risk mitigation
  3. 3 Calculate actual required sample size using Python (scipy.stats) and compare to user's estimate
  4. 4 Provide structured feedback with scores across metric selection, statistical rigor, variant design, and PM judgment
  5. 5 Present improved test design with all calculated values and professional formatting

What You'll Need

  • Python with scipy for statistical calculations
  • User provides complete test design or metrics framework when prompted
  • Basic understanding of A/B testing concepts (skill teaches statistical details)